Diagnostics and Intervention in Developmental Dyscalculia: Current Issues and Novel Perspectives

Moeller, Korbinian; Fischer, Ursula; Creß, Ulrike; Nuerk, Hans‐Christoph

doi:10.1007/978-94-007-4086-0_14

Cited by 27 publications

(28 citation statements)

References 162 publications

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“…This is further distinguished as deficit in processing number magnitude (33) or deficit in number sense (34). However, developmental literature is inconclusive and inconsistent as MD has a complex and heterogenous clinical presentation (35).…”

Section: Core Deficit Hypothesismentioning

confidence: 99%

Specific learning disability in mathematics: a comprehensive review

Soares¹,

Evans²,

Patel³

2018

Transl. Pediatr.

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Math skills are necessary for success in the childhood educational and future adult work environment. This article reviews the changing terminology for specific learning disabilities (SLD) in math and describes the emerging genetics and neuroimaging studies that relate to individuals with math disability (MD). It is important to maintain a developmental perspective on MD, as presentation changes with age, instruction, and the different models (educational and medical) of identification. Intervention requires a systematic approach to screening and remediation that has evolved with more evidence-based literature. Newer directions in behavioral, educational and novel interventions are described.

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Section: Core Deficit Hypothesismentioning

confidence: 99%

Specific learning disability in mathematics: a comprehensive review

Soares¹,

Evans²,

Patel³

2018

Transl. Pediatr.

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“…Based on empirical evidence different characteristics of effective treatments of children with DD are proposed in the literature. Treatment approaches are considered to be especially effective, when they are adaptive to the child's learning needs and learning speed (Burns et al, 2010;Moeller et al, 2012). Children with DD benefit from a structured design, hierarchical organization and frequent as well as constant repetition and practice (Fuchs et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Efficacy of a Computer-Based Learning Program in Children With Developmental Dyscalculia. What Influences Individual Responsiveness?

et al. 2020

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This study presents the evaluation of a computer-based learning program for children with developmental dyscalculia and focuses on factors affecting individual responsiveness. The adaptive training program Calcularis 2.0 has been developed according to current neuro-cognitive theory of numerical cognition. It aims to automatize number representations, supports the formation and access to the mental number line and trains arithmetic operations as well as arithmetic fact knowledge in expanding number ranges. Sixty-seven children with developmental dyscalculia from second to fifth grade (mean age 8.96 years) were randomly assigned to one of two groups (Calcularis group, waiting control group). Training duration comprised a minimum of 42 training sessions à 20 min within a maximum period of 13 weeks. Compared to the waiting control group, children of the Calcularis group demonstrated a higher benefit in arithmetic operations and number line estimation. These improvements were shown to be stable after a 3-months post training interval. In addition, this study examines which predictors accounted for training improvements. Results indicate that this self-directed training was especially beneficial for children with low math anxiety scores and without an additional reading and/or spelling disorder. In conclusion, Calcularis 2.0 supports children with developmental dyscalculia to improve their arithmetical abilities and their mental number line representation. However, it is relevant to further adapt the setting to the individual circumstances.

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“…For MD, research has indicated that impairments might exist in WM, leading to difficulty with executing calculation procedures and learning arithmetic facts (e.g., Schuchardt et al, 2008 ; Geary et al, 2009 ; Raghubar et al, 2010 ). In addition, a central deficit in the processing of number magnitude information might be related to MD (i.e., number sense, NS; Wilson and Dehaene, 2007 ; Landerl et al, 2009 ; Moeller et al, 2012 ; Kroesbergen and Van Dijk, 2015 ). However, whether these number processing deficiencies are specific to symbolic magnitudes (i.e., numbers; Rousselle and Noël, 2007 ) or also involve non-symbolic magnitudes (e.g., dots; Landerl et al, 2009 ; Moll et al, 2015 ) is still debated.…”

Section: Introductionmentioning

confidence: 99%

Shared and Unique Risk Factors Underlying Mathematical Disability and Reading and Spelling Disability

et al. 2016

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High comorbidity rates have been reported between mathematical learning disabilities (MD) and reading and spelling disabilities (RSD). Research has identified skills related to math, such as number sense (NS) and visuospatial working memory (visuospatial WM), as well as to literacy, such as phonological awareness (PA), rapid automatized naming (RAN) and verbal short-term memory (Verbal STM). In order to explain the high comorbidity rates between MD and RSD, 7–11-year-old children were assessed on a range of cognitive abilities related to literacy (PA, RAN, Verbal STM) and mathematical ability (visuospatial WM, NS). The group of children consisted of typically developing (TD) children (n = 32), children with MD (n = 26), children with RSD (n = 29), and combined MD and RSD (n = 43). It was hypothesized that, in line with the multiple deficit view on learning disorders, at least one unique predictor for both MD and RSD and a possible shared cognitive risk factor would be found to account for the comorbidity between the symptom dimensions literacy and math. Secondly, our hypotheses were that (a) a probabilistic multi-factorial risk factor model would provide a better fit to the data than a deterministic single risk factor model and (b) that a shared risk factor model would provide a better fit than the specific multi-factorial model. All our hypotheses were confirmed. NS and visuospatial WM were identified as unique cognitive predictors for MD, whereas PA and RAN were both associated with RSD. Also, a shared risk factor model with PA as a cognitive predictor for both RSD and MD fitted the data best, indicating that MD and RSD might co-occur due to a shared underlying deficit in phonological processing. Possible explanations are discussed in the context of sample selection and composition. This study shows that different cognitive factors play a role in mathematics and literacy, and that a phonological processing deficit might play a role in the occurrence of MD and RSD.

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Diagnostics and Intervention in Developmental Dyscalculia: Current Issues and Novel Perspectives

Cited by 27 publications

References 162 publications

Specific learning disability in mathematics: a comprehensive review

Specific learning disability in mathematics: a comprehensive review

Efficacy of a Computer-Based Learning Program in Children With Developmental Dyscalculia. What Influences Individual Responsiveness?

Shared and Unique Risk Factors Underlying Mathematical Disability and Reading and Spelling Disability

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